In this lecture, we solidify our geometric understanding of a confidence interval and further reinforce why interval estimation should always be preferred over point estimates. Some linear regression examples (with confidence intervals on regression coefficients) are demonstrated using data from the scientific literature. We then cover how to generate confidence intervals for 2-sample tests and use those pairwise confidence intervals with other techniques to do ranking and selection of more than 2 models within a simulation study. Thus, the main focus of this lecture is methods for comparing and contrasting among two-to-many simulation models.